Systems and methods for categorizing electronic messages for compliance reviews

ABSTRACT

The disclosed computer-implemented method for categorizing electronic messages for compliance reviews may include (1) identifying, as part of a compliance review for an organization, an uncategorized electronic message sent or received by a supervised user within the organization, (2) comparing the uncategorized electronic message with information gathered from previously categorized electronic messages sent or received by supervised users within the organization, (3) determining, based at least in part on the comparison, a relevance level of the uncategorized electronic message with respect to the compliance review, (4) receiving, from a compliance reviewer, feedback indicating whether the determined relevance level is correct, and (5) updating the previously gathered information based on the feedback from the compliance reviewer. Various other methods, systems, and computer-readable media are also disclosed.

CROSS REFERENCE TO RELATED APPLICATION

This application is a continuation of U.S. application Ser. No.14/737,521, filed Jun. 12, 2015, the disclosure of which isincorporated, in its entirety, by this reference.

BACKGROUND

Compliance reviews are an important but often tedious process intendedto ensure that employees are adhering to regulatory standards. Manydifferent industries (such as finance, manufacturing, andpharmaceuticals) may have regulations that require companies to monitor,supervise, and/or review their employees in some capacity. Some of theseregulations may require companies to monitor, supervise, and/or reviewemployees' electronic communications (such as emails and/or instantmessages). With hundreds or even thousands of employees sending and/orreceiving electronic communications on a daily basis and only a limitednumber of compliance reviewers, each review of such electroniccommunications for compliance purposes may amount to a difficult and/ortime-consuming task.

The instant disclosure, therefore, identifies and addresses a need forsystems and methods for categorizing electronic messages for compliancereviews to increase the efficiency, accuracy, and/or reliability of suchcompliance reviews.

SUMMARY

As will be described in greater detail below, the instant disclosuredescribes various systems and methods for categorizing electronicmessages for compliance reviews by automatically assigning relevanceratings to messages based at least in part on previously categorizedmessages with similar characteristics.

In one example, a computer-implemented method for categorizingelectronic messages for compliance reviews may include (1) identifying,as part of a compliance review for an organization, an uncategorizedelectronic message sent or received by a supervised user within theorganization, (2) comparing the uncategorized electronic message withinformation gathered from previously categorized electronic messagessent or received by supervised users within the organization, (3)determining, based at least in part on the comparison, a relevance levelof the uncategorized electronic message with respect to the compliancereview, (4) receiving, from a compliance reviewer, feedback indicatingwhether the determined relevance level is correct, and (5) updating thepreviously gathered information based on the feedback from thecompliance reviewer.

In one embodiment, the compliance review may include and/or represent anexamination, by the compliance reviewer, of at least a subset of allelectronic messages sent or received by the supervised users within theorganization. In this embodiment, the compliance review may facilitatedetermining whether the portion of electronic messages sent or receivedby the supervised users include any evidence of inappropriate activityby the supervised users.

In some examples, determining the relevance level of the uncategorizedelectronic message may include examining the uncategorized electronicmessage for any evidence indicating whether the uncategorized electronicmessage is an organization-wide mass communication and determining,based at least in part on the examination of the uncategorizedelectronic message, the relevance level of the uncategorized electronicmessage. Additionally or alternatively, determining the relevance levelof the uncategorized electronic message may include assigning, to theuncategorized electronic message, a high relevance level that is above arelevance threshold due at least in part to examined evidence indicatingthat the uncategorized electronic message is not an organization-widemass communication and/or assigning, to the uncategorized electronicmessage, a low relevance level that is below a relevance threshold dueat least in part to examined evidence indicating that the uncategorizedelectronic message is an organization-wide mass communication.

In some examples, comparing the uncategorized electronic message withthe information gathered from the previously categorized electronicmessages may include comparing a recipient of the uncategorizedelectronic message to a recipient of at least one previously categorizedelectronic message. In further examples, comparing the uncategorizedelectronic message with the information gathered from the previouslycategorized electronic messages may include comparing a sender of theuncategorized electronic message to a sender of at least one previouslycategorized electronic message. In one example, comparing theuncategorized electronic message with the information gathered from thepreviously categorized electronic messages may include comparing akeyword in the uncategorized electronic message to a keyword in at leastone previously categorized electronic message.

Additionally or alternatively, comparing the uncategorized electronicmessage with the information gathered from the previously categorizedelectronic messages may include comparing a word frequency statisticderived from the uncategorized electronic message to a word frequencystatistic derived from at least one previously categorized electronicmessage. In some examples, comparing the uncategorized electronicmessage with the information gathered from the previously categorizedelectronic messages may include comparing metadata about theuncategorized electronic message to metadata from at least onepreviously categorized electronic message. Additionally oralternatively, comparing the uncategorized electronic message with theinformation gathered from previously categorized electronic messages mayinclude comparing a subject, a direction relative to the organization, adomain of a sender, and/or a domain of a recipient of the electronicmessage with a subject, a direction relative to the organization, adomain of a sender, and/or a domain of a recipient from at least onepreviously categorized electronic message.

In one embodiment, the computer-implemented method may further include(1) collecting relevance levels assigned to the previously categorizedelectronic messages, (2) comparing the relevance level of theuncategorized electronic message to the relevance levels assigned to thepreviously categorized electronic messages, (3) ranking, based at leastin part on the relevance levels, a set of electronic messages thatinclude the uncategorized electronic message and the previouslycategorized electronic messages, and (4) providing the ranked set ofelectronic messages to the compliance reviewer as part of the compliancereview. In some examples, the computer-implemented method may furtherinclude deleting the information gathered from the previouslycategorized electronic messages upon completion of the compliance reviewand initiation of a new compliance review for the organization.

In one example, determining the relevance level of the uncategorizedelectronic message may include determining that the uncategorizedelectronic message is substantially relevant to the compliance review,and receiving the feedback indicating whether the determined relevancelevel is correct may include receiving feedback indicating that therelevance level is incorrect and the uncategorized electronic message issubstantially irrelevant to the compliance review. In this example,updating the previously gathered information based on the feedback mayinclude updating the previously gathered information to indicate thatthe uncategorized electronic message is substantially irrelevant to thecompliance review.

In another example, determining the relevance level of the uncategorizedelectronic message may include determining that the uncategorizedelectronic message is substantially irrelevant to the compliance review,and receiving the feedback indicating whether the determined relevancelevel is correct may include receiving feedback indicating that therelevance level is incorrect and the uncategorized electronic message issubstantially relevant to the compliance review. In this example,updating the previously gathered information based on the feedback mayinclude updating the previously gathered information to indicate thatthe uncategorized electronic message is substantially relevant to thecompliance review.

In one embodiment, a system for implementing the above-described methodmay include (1) an identification module, stored in memory, thatidentifies, as part of a compliance review for an organization, anuncategorized electronic message sent or received by a supervised userwithin the organization, (2) a comparison module, stored in memory, thatcompares the uncategorized electronic message with information gatheredfrom previously categorized electronic messages sent or received bysupervised users within the organization, (3) a determination module,stored in memory, that determines, based at least in part on thecomparison, a relevance level of the uncategorized electronic messagewith respect to the compliance review, (4) a receiving module, stored inmemory, that receives, from a compliance reviewer, feedback indicatingwhether the determined relevance level is correct, (5) an updatingmodule, stored in memory, that updates the previously gatheredinformation based on the feedback from the compliance reviewer, and (6)at least one physical processor configured to execute the identificationmodule, the comparison module, the determination module, the receivingmodule, and the updating module.

In some examples, the above-described method may be encoded ascomputer-readable instructions on a non-transitory computer-readablemedium. For example, a computer-readable medium may include one or morecomputer-executable instructions that, when executed by at least oneprocessor of a computing device, may cause the computing device to (1)identify, as part of a compliance review for an organization, anuncategorized electronic message sent or received by a supervised userwithin the organization, (2) compare the uncategorized electronicmessage with information gathered from previously categorized electronicmessages sent or received by supervised users within the organization,(3) determine, based at least in part on the comparison, a relevancelevel of the uncategorized electronic message with respect to thecompliance review, (4) receive, from a compliance reviewer, feedbackindicating whether the determined relevance level is correct, and (5)update the previously gathered information based on the feedback fromthe compliance reviewer.

Features from any of the above-mentioned embodiments may be used incombination with one another in accordance with the general principlesdescribed herein. These and other embodiments, features, and advantageswill be more fully understood upon reading the following detaileddescription in conjunction with the accompanying drawings and claims.

BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying drawings illustrate a number of exemplary embodimentsand are a part of the specification. Together with the followingdescription, these drawings demonstrate and explain various principlesof the instant disclosure.

FIG. 1 is a block diagram of an exemplary system for categorizingelectronic messages for compliance reviews.

FIG. 2 is a block diagram of an additional exemplary system forcategorizing electronic messages for compliance reviews.

FIG. 3 is a flow diagram of an exemplary method for categorizingelectronic messages for compliance reviews.

FIG. 4 is a block diagram of an additional exemplary system forcategorizing electronic messages for compliance reviews.

FIG. 5 is a block diagram of an additional exemplary system forcategorizing electronic messages for compliance reviews.

FIG. 6 is a block diagram of an exemplary computing system capable ofimplementing one or more of the embodiments described and/or illustratedherein.

FIG. 7 is a block diagram of an exemplary computing network capable ofimplementing one or more of the embodiments described and/or illustratedherein.

Throughout the drawings, identical reference characters and descriptionsindicate similar, but not necessarily identical, elements. While theexemplary embodiments described herein are susceptible to variousmodifications and alternative forms, specific embodiments have beenshown byway of example in the drawings and will be described in detailherein. However, the exemplary embodiments described herein are notintended to be limited to the particular forms disclosed. Rather, theinstant disclosure covers all modifications, equivalents, andalternatives falling within the scope of the appended claims.

DETAILED DESCRIPTION OF EXEMPLARY EMBODIMENTS

The present disclosure is generally directed to systems and methods forcategorizing electronic messages for compliance reviews. As will beexplained in greater detail below, by automatically assigning relevancelevels to messages and presenting reviewers with messages sorted byrelevance, the systems and methods described herein may enable reviewersto more efficiently and effectively examine large quantities of messagesfor evidence of inappropriate behavior. By categorizing messages bytheir likely relevance, continually using feedback from reviewers toimprove the categorization algorithm, and presenting ever-more-relevantmessages, the systems described herein may create a self-improvingrelevancy categorization mechanism that continuously improves theefficiency and effectiveness of compliance reviews. Increasing theefficiency of compliance reviews may allow organizations to expend fewerresources on compliance reviews while catching regulatory violationsmore quickly and effectively than before.

The following will provide, with reference to FIGS. 1-2 and 4-5,detailed descriptions of exemplary systems for categorizing electronicmessages for compliance reviews. Detailed descriptions of correspondingcomputer-implemented methods will also be provided in connection withFIG. 3. In addition, detailed descriptions of an exemplary computingsystem and network architecture capable of implementing one or more ofthe embodiments described herein will be provided in connection withFIGS. 6 and 7, respectively.

FIG. 1 is a block diagram of exemplary system 100 for categorizingelectronic messages for compliance reviews. As illustrated in thisfigure, exemplary system 100 may include one or more modules 102 forperforming one or more tasks. For example, and as will be explained ingreater detail below, exemplary system 100 may include an identificationmodule 104 that identifies, as part of a compliance review for anorganization, an uncategorized electronic message sent or received by asupervised user within the organization. Exemplary system 100 mayadditionally include a comparison module 106 that compares theuncategorized electronic message with information gathered frompreviously categorized electronic messages sent or received bysupervised users within the organization.

Exemplary system 100 may also include a determination module 108 thatdetermines, based at least in part on the comparison, a relevance levelof the uncategorized electronic message with respect to the compliancereview. Exemplary system 100 may additionally include a receiving module110 that receives, from a compliance reviewer, feedback indicatingwhether the determined relevance level may be correct. Exemplary system100 may also include an updating module 112 that updates the previouslygathered information based on the feedback from the compliance reviewer.Although illustrated as separate elements, one or more of modules 102 inFIG. 1 may represent portions of a single module or application.

In certain embodiments, one or more of modules 102 in FIG. 1 mayrepresent one or more software applications or programs that, whenexecuted by a computing device, cause the computing device to performone or more tasks. For example, and as will be described in greaterdetail below, one or more of modules 102 may represent software modulesstored and configured to run on one or more computing devices, such asthe devices illustrated in FIG. 2 (e.g., computing devices 202(1)-202(n)and/or server 206), computing system 610 in FIG. 6, and/or portions ofexemplary network architecture 700 in FIG. 7. One or more of modules 102in FIG. 1 may also represent all or portions of one or morespecial-purpose computers configured to perform one or more tasks.

As illustrated in FIG. 1, exemplary system 100 may also include one ormore databases, such as database 120. In one example, database 120 maybe configured to store previously gathered information 122 aboutpreviously categorized emails. The term “previously gatheredinformation” or “information gathered from previously categorizedelectronic messages,” as used herein, generally refers to anyinformation and/or data about characteristics of a message that suggestrelevance or irrelevance to a compliance review. In some examples,previously gathered information 122 may include a manually created dataset that is composed of messages manually categorized by compliancereviewers during the current compliance review and/or one or moreprevious compliance reviews.

In other examples, the previously gathered information 122 may includeinformation that the systems described herein have generated based onfeedback from one or more compliance reviewers. In some examples,previously gathered information 122 may include information gatheredover the course of several compliance reviews, while in other examples,previously gathered information 122 may only include informationgathered in the course of the current compliance review. In someembodiments, the set of previously gathered information may be empty atthe start of a compliance review and/or the systems described herein mayonly automatically categorize messages after a certain threshold forpreviously gathered information is reached.

Database 120 may represent portions of a single database or computingdevice or a plurality of databases or computing devices. For example,database 120 may represent a portion of server 206 in FIG. 2, computingsystem 610 in FIG. 6, and/or portions of exemplary network architecture700 in FIG. 7. Alternatively, database 120 in FIG. 1 may represent oneor more physically separate devices capable of being accessed by acomputing device, such as server 206 in FIG. 2, computing system 610 inFIG. 6, and/or portions of exemplary network architecture 700 in FIG. 7.

Exemplary system 100 in FIG. 1 may be implemented in a variety of ways.For example, all or a portion of exemplary system 100 may representportions of exemplary system 200 in FIG. 2. As shown in FIG. 2, system200 may include one or more computing devices 202(1)-202(n) incommunication with a server 206 via a network 204. In one example,computing devices 202(1)-202(n) may be programmed with one or more ofmodules 102 and/or may store all or a portion of the data in database120. Additionally or alternatively, server 206 may be programmed withone or more of modules 102 and/or may store all or a portion of the datain database 120.

In one embodiment, one or more of modules 102 from FIG. 1 may, whenexecuted by at least one processor of computing devices 202(1)-202(n)and/or server 206, enable computing devices 202(1)-202(n) and/or server206 to categorize electronic messages for compliance reviews. Forexample, and as will be described in greater detail below,identification module 104 may identify, as part of a compliance reviewfor an organization, an uncategorized electronic message 208 sent orreceived by a supervised user within the organization. Afteruncategorized electronic message 208 has been identified, comparisonmodule 106 may compare uncategorized electronic message 208 withinformation 122 gathered from previously categorized electronic messagessent or received by supervised users within the organization. Next,determination module 108 may determine, based at least in part on thecomparison, a relevance level 210 of uncategorized electronic message208 with respect to the compliance review. At some later time, receivingmodule 110 may receive, from a compliance reviewer, feedback 212indicating whether the determined relevance level 210 is correct.Finally, updating module 112 may update previously gathered information122 based on feedback 212 from the compliance reviewer.

Computing devices 202(1)-202(n) generally represents any type or form ofcomputing devices capable of reading computer-executable instructions.Examples of computing devices 202(1)-202(n) include, without limitation,laptops, tablets, desktops, servers, cellular phones, Personal DigitalAssistants (PDAs), multimedia players, embedded systems, wearabledevices (e.g., smart watches, smart glasses, etc.), gaming consoles,combinations of one or more of the same, exemplary computing system 610in FIG. 6, or any other suitable computing device.

Server 206 generally represents any type or form of computing devicecapable of categorizing emails for compliance reviews. Examples ofserver 206 include, without limitation, application servers, securityservers, web servers, storage servers, policy and/or compliance servers,deduplication servers, and/or database servers configured to run certainsoftware applications and/or provide various security, web, storage,policy, compliance deduplication, and/or database services.

Network 204 generally represents any medium or architecture capable offacilitating communication or data transfer. Examples of network 204include, without limitation, an intranet, a Wide Area Network (WAN), aLocal Area Network (LAN), a Personal Area Network (PAN), the Internet,Power Line Communications (PLC), a cellular network (e.g., a GlobalSystem for Mobile Communications (GSM) network), exemplary networkarchitecture 700 in FIG. 7, or the like. Network 204 may facilitatecommunication or data transfer using wireless or wired connections. Inone embodiment, network 204 may facilitate communication betweencomputing devices 202(1)-202(n) and server 206.

Uncategorized electronic message 208 generally represents any type ofelectronic message sent or received using a computing device. In oneexample, uncategorized electronic message 208 may include and/orrepresent any message sent from one individual, group, and/or server toanother via electronic means. An electronic message may include text,pictures, video, audio, and/or other files. Some examples ofuncategorized electronic message 208 include, without limitation, anemail, a text message, an instant message, a chat message (e.g., viaGCHAT and/or internet relay chat (IRC)), a social networking websitemessage (e.g., via LINKEDIN and/or FACEBOOK), and/or an audio calland/or meeting (e.g., via SKYPE and/or LYNC).

Relevance level 210 generally represents any categorical determinationof likely relevance to a compliance review. In some examples, relevancelevel 210 may include two options, “relevant” and “not relevant.” Inother examples, relevance level 210 may include multiple options, suchas, “irrelevant,” “unlikely to be relevant,” “probably relevant,” and/or“highly relevant.” In some embodiments, relevance level 210 may match arelevance level system used by compliance reviewers. For example, acompliance review may mandate that reviewers mark emails as,“irrelevant,” “questionable,” and/or “escalate to supervisor.” In thisexample, the systems described herein may categorized emails as“potentially irrelevant,” “potentially questionable,” and/or“potentially escalate to supervisor.” In some examples, regulations mayprohibit automated systems from influencing reviewers. In theseexamples, relevance level 210 may be presented as “highlighted” and “nothighlighted.” Additionally or alternatively, relevance level 210 mayinclude a numerical score, such as a percentage probability that themessage is relevant to the compliance review.

Feedback 212 generally represents any input entered by and/or receivedfrom a compliance reviewer. In one example, feedback 212 may indicate arelevance level of a message. Additionally or alternatively, feedback212 may indicate whether a relevance level is accurate and/orinaccurate. Examples of feedback 212, without limitation, pushing abutton that indicates whether or not a calculated relevance level of amessage is correct, selecting a relevance level of a message from alist, and/or taking an action that implies a relevance level of amessage. For example, a compliance reviewer may provide feedback 212 byescalating a message to his or her supervisor, thereby implying that themessage is highly relevant. In another example, a compliance reviewermay provide feedback 212 more directly by checking a box labeled“calculated compliance level is correct.”

FIG. 3 is a flow diagram of an exemplary computer-implemented method 300for categorizing electronic messages for compliance reviews. The stepsshown in FIG. 3 may be performed by any suitable computer-executablecode and/or computing system. In some embodiments, the steps shown inFIG. 3 may be performed by one or more of the components of system 100in FIG. 1, system 200 in FIG. 2, computing system 610 in FIG. 6, and/orportions of exemplary network architecture 700 in FIG. 7.

As illustrated in FIG. 3, at step 302, one or more of the systemsdescribed herein may identify, as part of a compliance review for anorganization, an uncategorized electronic message sent or received by asupervised user within the organization. For example, identificationmodule 104 may, as part of server 206 in FIG. 2, identify, as part of acompliance review for an organization, uncategorized electronic message208 sent or received by a supervised user within the organization.

The term “compliance review,” as used herein, generally refers to anytype or form of review of communications and/or behavior of certainemployees of an organization. In one example, a compliance review may beperformed in an attempt to comply with regulatory compliancerequirements. Additionally or alternatively, a compliance review may beperformed in an attempt to ensure that users and/or employees are notviolating certain organizational guidelines and/or policies (such assexual harassment policies).

In some examples, a compliance review may include an examination by oneor more compliance reviewers of at least a subset of all electronicmessages sent or received by the supervised users within theorganization. In these examples, the compliance reviewers may attempt todetermine whether the portion of electronic messages sent or received bythe supervised users includes any evidence of inappropriate activity bythe supervised users. Such inappropriate activity may include and/orrepresent illegal and/or unethical activity (e.g., sexual harassment,insider trading, price fixing, and/or insecure handling of confidentialdata).

The term “supervised user,” as used herein, generally refers to anyuser, employee, and/or member whose behavior and/or communications aresubjected to a compliance review. In some examples, a supervised usermay be any employee of an organization. In other examples, a superviseduser may be a certain category of employee. For example, a regulationmay mandate that all employees with access to customer financial data(such as brokers) be supervised and/or monitored, but employees withoutsuch access (such as human resources personnel) may not require suchsupervision or monitoring. Additionally or alternatively, a superviseduser may be a specific user who has come under scrutiny for possibleinappropriate behavior.

Identification module 104 may identify uncategorized electronic message208 in a variety of ways and/or contexts. For example, identificationmodule 104 may identify any message sent from or to a supervised user asan eligible message for the compliance review. In some examples,identification module 104 may only identify messages after the messageshave passed through a spam filter and/or malware detection system andhave been classified as non-malicious non-spam messages. In someinstances, regulations may require a reviewer to examine a randomlysampled percentage of messages sent or received within an organization.In these instances, identification module 104 may identify a randomsubset of messages as candidates for the compliance review.

At step 304 in FIG. 3, one or more of the systems described herein maycompare the uncategorized electronic message with information gatheredfrom previously categorized electronic messages sent or received bysupervised users within the organization. For example, comparison module106 may, as part of server 206 in FIG. 2, compare uncategorizedelectronic message 208 with information 122 gathered from previouslycategorized electronic messages sent or received by supervised userswithin the organization.

Comparison module 106 may compare uncategorized electronic message 208with previously gathered information 122 in a variety of ways. Forexample, comparison module 106 may compare uncategorized electronicmessage 208 with previously categorized messages in order to determinethe relevance level of the previously categorized messages with thegreatest similarity to the uncategorized message. In one example,comparison module 106 may compare several different messagecharacteristics of uncategorized electronic message 208 withcharacteristics of previously categorized messages and/or may weight themessage characteristics in order to determine overall similarity.

In some examples, comparison module 106 may compare uncategorizedelectronic message 208 with previously gathered information 122 bycomparing a recipient, a sender, one or more keywords and/or keyphrases, a word frequency statistic, a subject, a direction relative tothe organization (e.g., from an internal email address to an externalemail address or vice versa), a domain of a sender, a domain of arecipient, and/or additional metadata of uncategorized electronicmessage 208 to a recipient, a sender, one or more keywords and/or keyphrases, a word frequency statistic, a subject, a direction, a domain ofa sender, a domain of a recipient, and/or additional metadata of atleast one previously categorized electronic message. In someembodiments, a recipient may include an email address in the “to,” “cc,”and/or “bcc” field of an email and/or recipients in the various fieldsmay be treated differently with respect to potential relevance. Forexample, a message with one or more recipients in the “bcc” field may bemore likely to be relevant to the compliance review than a message withno recipients in the “bcc” field. In some embodiments, a keyword mayinclude a word stem. For example, a keyword “embezzl” may match on thewords “embezzler,” “embezzling,” “embezzled” and/or “embezzle.”

In one example, if previous messages from or to a certain user havetypically been marked as relevant, comparison module 106 may report thatuncategorized electronic message 208 is similar to messages determinedto be relevant. In another example, previously categorized messages thatinclude the phrase “financial news” one or more times may have beenmarked as highly relevant. In this example, uncategorized electronicmessage 208 may be highly relevant if it includes several mentions ofthe phrase “financial news.” In another example, messages that includethe phrase “financial news” but also include the phrase “annual publicsummary” may have been previously categorized as not relevant.

In another example, previously categorized messages sent duringnon-working hours, such as between 6 p.m. and 5 a.m., may have been morelikely to be categorized as relevant. In this example, if uncategorizedelectronic message 208 was sent at 1 A.M., comparison module 106 mayreport that uncategorized electronic message 208 is similar to messagesmarked as relevant.

At step 306 in FIG. 3, one or more of the systems described herein maydetermine, based at least in part on the comparison, a relevance levelof the uncategorized electronic message with respect to the compliancereview. For example, determination module 108 may, as part of server 206in FIG. 2, determine, based at least in part on the comparison,relevance level 210 of uncategorized electronic message 208 with respectto the compliance review.

Determination module 108 may determine relevance level 210 ofuncategorized electronic message 208 in a variety of ways. For example,determination module 108 may use information about the relevance levelof similar messages and/or pre-defined rules for compliance reviewrelevance to determine relevance level 210. Additionally oralternatively, determination module 108 may determine relevance level210 based at least in part on the sender and/or recipient ofuncategorized electronic message 208.

As a specific example, determination module 108 may determine therelevance levels of electronic messages exchanged within an organizationin connection with exemplary implementation 400 in FIG. 4. Asillustrated in FIG. 4, implementation 400 may involve organizationemployees 402 communicating with each other and/or with external usersand/or lists. In this example, organization employees 402 may include afacilities user 404, a finance user 406, an admin user 408, and/or asuspicious user 410. In one example, facilities user 404 may regularlycommunicate with users in many departments as part of his or her job.Accordingly, communication between facilities user 404 and finance user406 and/or admin user 408 may not be suspicious and, as a result, may beunlikely to be relevant to a compliance review.

In one example, finance user 406 may not typically communicate withadmin user 408 and/or may only communicate about certain subjects and/ortopics. As a result, some communications between finance user 406 andadmin user 408 may be suspicious and thus may be relevant to thecompliance review. In some examples, determination module 108 may onlymark messages exchanged between finance user 406 and admin user 408 asrelevant to the compliance review if the messages include keywordsidentified as appearing in highly relevant messages.

In some examples, suspicious user 410 may be an employee of theorganization who is under suspicion for inappropriate behavior. In theseexamples, any messages sent to or from suspicious user 410 may besubject to increased scrutiny and thus determination module 108 may markall such messages as relevant. In some examples, one or more supervisedusers, such as finance user 406 and/or suspicious user 410, may besubscribed to a listserv 412. Listserv 412 may send irrelevant massmessages such as newsletters, coupons, and/or public discussions thatare hardly relevant to a compliance review. In some embodiments,determination module 108 may categorize all messages sent to or fromlistserv 412 as irrelevant even if those messages would otherwise bemarked as relevant. In some examples, communication with non-employees,such as an external user 414, may be suspicious and/or inherentlyinappropriate. In these examples, determination module 108 may determinethat all messages sent to or from external user 414 are relevant to thecompliance review.

In some examples, determination module 108 may determine relevance level210 by examining uncategorized electronic message 208 for any evidenceindicating whether uncategorized electronic message 208 is anorganization-wide mass communication such as a scheduled report, anevent invitation, an announcement, and/or any other type innocuous masscommunication. In some examples, determination module 108 may assignuncategorized electronic message 208 a high relevance level that isabove a relevance threshold due at least in part to examined evidenceindicating that uncategorized electronic message 208 is not anorganization-wide mass communication. Additionally or alternatively,determination module 108 may assign a low relevance level that is belowthe relevance threshold due at least in part to examined evidenceindicating that uncategorized electronic message 208 is anorganization-wide mass communication. For example, determination module108 may determine that an email sent to at least 80% of an organizationshould be categorized as irrelevant. In another example, determinationmodule 108 may determine that any email sent to more than half of acompany that includes keywords such as “picnic,” “fundraiser,” and/or“team-building” may be irrelevant. Additionally or alternatively,determination module 108 may determine that an email sent to 10% of anorganization is not a mass communication and is relevant.

In some embodiments, determination module 108 may determine relevancelevels for multiple messages and present the categorized messages to thecompliance reviewer in a list. In one example, the systems describedherein may collect relevance levels assigned to previously categorizedelectronic messages that have been recently categorized and have not yetbeen presented to a compliance reviewer and may compare the relevancelevel of electronic message 208 to the relevance levels assigned to therecently categorized electronic messages. The systems described hereinmay then rank, based at least in part on the relevance level ofelectronic message 208 and the relevance levels of the recentlycategorized electronic messages, a set of electronic messages thatincludes electronic message 208 and the recently categorized electronicmessages and may provide the ranked set of electronic messages to thecompliance reviewer as part of the compliance review. For example, thesystems described herein may list the ranked messages in order from“highly relevant,” to “possibly relevant,” to “not relevant.” In anotherembodiment, the system described herein may list the ranked messages inorder of likely relevance and/or may visually highlight any messageswith a relevance level that exceeds a certain threshold.

In some examples, regulations may require that a compliance reviewerexamine a certain portion of messages. In some embodiments, the systemsdescribed herein may create a review set of the most likely to berelevant messages for display to the compliance reviewer. For example, aregulation may require a reviewer to examine 3% of emails sent orreceived within an organization. In this example, the systems describedherein may present a ranked set of the top 3% of emails most likely tobe relevant as categorized by the systems described herein.

Returning to FIG. 3, at step 308, one or more of the systems describedherein may receive, from a compliance reviewer, feedback indicatingwhether the determined relevance level is correct. For example,receiving module 110 may, as part of server 206 in FIG. 2, receive, froma compliance reviewer, feedback 212 indicating whether the determinedrelevance level 210 is correct and/or accurate. In other words, feedback212 may indicate whether message 208 was correctly and/or accuratelycategorized in terms of relevancy with respect to the compliance review.

Receiving module 110 may receive feedback 212 from a compliance reviewerin a variety of ways. In some examples, a compliance reviewer mayintentionally provide feedback 212 to receiving module 110. In one suchexample, a compliance reviewer may press a button that indicates whetheror not relevance level 210 for electronic message 208 is correct and/oraccurate.

In another example, a reviewer may select the correct relevance levelfrom a dropdown list in order to provide feedback 212. In otherembodiments, receiving module 110 may infer feedback 212 from acompliance reviewer's actions. For example, a compliance reviewer maydelete electronic message 208 from his or her review queue withoutopening it. This deletion may imply that the reviewer considerselectronic message 208 to be irrelevant. In another example, acompliance reviewer may flag electronic message 208 for further researchand/or may forward electronic message 208 to his or her supervisor. Thisflagging and/or forwarding may indicate that the reviewer considerselectronic message 208 to be highly relevant.

In some examples, a compliance reviewer may highlight important words orphrases in electronic message 208. In these examples, receiving module110 may receive the feedback that the highlighted words or phrasesshould be positively weighted when determining the relevance of futuremessages.

At step 310 in FIG. 3, one or more of the systems described herein mayupdate the previously gathered information based on the feedback fromthe compliance reviewer. For example, updating module 112 may, as partof server 206 in FIG. 2, update previously gathered information 122based on feedback 212 from the compliance reviewer.

Updating module 112 may update previously gathered information 122 in avariety of ways and/or contexts. For example, updating module 112 mayupdate previously gathered information 122 when a reviewer indicatesthat relevance level 210 for message 208 is incorrect. In this example,updating module 112 may update previously gathered information 122 bylowering the weight of the factors that led to message 208 beingincorrectly categorized as relevant. In other embodiments, updatingmodule 112 may also update previously gathered information 122 when areviewer confirms that relevance level 210 is correct. In one example,updating module 112 may update previously gathered information 122 byassigning a higher weight to keywords that appeared frequently in a setof emails that a reviewer has recently categorized as relevant. Inanother example, updating module 112 may lower the weight of an item ofmetadata that was found in a message that a reviewer categorized as notrelevant.

In some examples, updating module 112 may update previously gatheredinformation 122 by adding information about electronic message 208 topreviously gathered information 122. For example, relevance level 210may indicate and/or suggest that electronic message 208 is substantiallyrelevant to the compliance review. In this example, receiving module 110may receive feedback 212 indicating that relevance level 210 isincorrect and electronic message 208 is substantially irrelevant to thecompliance review. As a result, updating module 112 may updatepreviously gathered information 122 based on feedback 212 by modifyingpreviously gathered information 122 to indicate that electronic message208 is substantially irrelevant to the compliance review. Additionallyor alternatively, updating module 112 may decrease the weight ofcharacteristics that were used to determine that electronic message 108was relevant.

In another example, updating module 112 may update previously gatheredinformation 122 by adding different information about electronic message208 to previously gathered information 112. For example, relevance level210 may indicate and/or suggest that electronic message 208 issubstantially irrelevant to the compliance review. In this example,receiving module 110 may receive feedback 212 indicating that relevancelevel 210 is incorrect and electronic message 208 is substantiallyrelevant to the compliance review. As a result, updating module 112 mayupdate previously gathered information 122 based on feedback 212 bymodifying previously gathered information 122 to indicate thatelectronic message 208 is substantially relevant to the compliancereview. Additionally or alternatively, updating module 112 may increasethe weight of characteristics of electronic message 208.

In some examples, systems described herein may delete previouslygathered information 122 upon completion of the compliance review andinitiation of a new compliance review for the organization. For example,the standards of a regulatory agency may change between compliancereviews, and previously irrelevant messages may now be relevant and viceversa. In another example, employees, company focus, organizationalstructure, and/or corporate culture may change during the time betweencompliance reviews, causing a shift in messaging patterns and/or keywordusage that renders the previous data set ineffective at categorizingrelevant messages.

In some examples, different types of compliance reviews may havedifferent needs. For example, one compliance review may be undertaken toensure that employees are not disclosing confidential information, whileanother may be initiated to ensure that employees are not violatingsexual harassment policies. In this example, the algorithms that detectmessages relevant to the former review may be less useful at findingmessages that are relevant to the latter review. By clearing out-of-dateinformation and beginning a new data set, the systems described hereinmay be able to more accurately determine relevance levels for electronicmessages that are part of the new compliance review.

The systems and methods described herein may be implemented in a numberof ways. FIG. 5 is a block diagram of an exemplary computing system 500for categorizing electronic messages for compliance reviews. Asillustrated in FIG. 5, database 120 may include previously categorizedemails 504 and/or previously gathered information 122 that has beenformulated based on previously categorized emails 504. For example, if alarge number of previously categorized emails 504 that were categorizedas relevant included the keywords “stocks,” “increasing,” and/or“shares,” while only a small number of irrelevant emails withinpreviously categorized emails 504 include those keywords, previouslygathered information 122 may include a listing of the words “stocks,”“increasing,” and/or “shares” along with high weights for potentialrelevance. Modules 102 may use previously gathered information 122 toevaluate uncategorized emails, such as an uncategorized email 506.

Uncategorized email 506 may first be processed by pre-processor 508.Pre-processor 508 may format and/or parse uncategorized email 506 sothat modules 102 can easily compare uncategorized email 506 topreviously gathered information 122. For example, pre-processor 508 mayextract and/or format text, metadata, attachments, images, signatures,markup, and the like. Modules 102 may analyze uncategorized email 506and assign it a probable relevance level before adding it to the pool ofcategorized emails 510. The systems described herein may displaycategorized emails 510 to one or more reviewers 512. Reviewers 512 maytake actions on any or all of categorized emails 510 and/or may sendfeedback to modules 102, which modules 102 may use to improve theeffectiveness of previously gathered information 122. As the nextuncategorized email arrives, modules 102 may use the updated previouslygathered information 122 to more accurately predict the probablerelevance level, thereby improving the quality of categorized emails510. The systems described herein may use each item of feedback fromreviewers 512 to improve previously gathered information 122,continuously improving the quality of categorized emails 510, and/orincreasing the efficiency of reviewers 512.

As explained in connection with method 300 above, the systems andmethods described herein may improve the quality of a compliance reviewset by automatically categorizing messages based on similarity topreviously categorized messages. The systems described herein mayanalyze word frequency in messages and/or other message properties inorder to determine which messages are most likely to be relevant. Once areviewer has manually determined whether a message is relevant or not,the systems described herein may use feedback from the reviewer toimprove the effectiveness of the data set that facilitates the initialcategorization of certain messages. By presenting a reviewer with asorted list of the messages most likely to be relevant, the systemsdescribed herein may reduce the amount of time needed for a reviewer toexamine the most relevant messages and/or decrease the chances that areviewer may miss an important message. By allowing reviewers to findrelevant information more quickly, the systems described herein mayreduce the burden of regulatory compliance for organizations.

FIG. 6 is a block diagram of an exemplary computing system 610 capableof implementing one or more of the embodiments described and/orillustrated herein. For example, all or a portion of computing system610 may perform and/or be a means for performing, either alone or incombination with other elements, one or more of the steps describedherein (such as one or more of the steps illustrated in FIG. 3). All ora portion of computing system 610 may also perform and/or be a means forperforming any other steps, methods, or processes described and/orillustrated herein.

Computing system 610 broadly represents any single or multi-processorcomputing device or system capable of executing computer-readableinstructions. Examples of computing system 610 include, withoutlimitation, workstations, laptops, client-side terminals, servers,distributed computing systems, handheld devices, or any other computingsystem or device. In its most basic configuration, computing system 610may include at least one processor 614 and a system memory 616.

Processor 614 generally represents any type or form of physicalprocessing unit (e.g., a hardware-implemented central processing unit)capable of processing data or interpreting and executing instructions.In certain embodiments, processor 614 may receive instructions from asoftware application or module. These instructions may cause processor614 to perform the functions of one or more of the exemplary embodimentsdescribed and/or illustrated herein.

System memory 616 generally represents any type or form of volatile ornon-volatile storage device or medium capable of storing data and/orother computer-readable instructions. Examples of system memory 616include, without limitation, Random Access Memory (RAM), Read OnlyMemory (ROM), flash memory, or any other suitable memory device.Although not required, in certain embodiments computing system 610 mayinclude both a volatile memory unit (such as, for example, system memory616) and a non-volatile storage device (such as, for example, primarystorage device 632, as described in detail below). In one example, oneor more of modules 102 from FIG. 1 may be loaded into system memory 616.

In certain embodiments, exemplary computing system 610 may also includeone or more components or elements in addition to processor 614 andsystem memory 616. For example, as illustrated in FIG. 6, computingsystem 610 may include a memory controller 618, an Input/Output (I/O)controller 620, and a communication interface 622, each of which may beinterconnected via a communication infrastructure 612. Communicationinfrastructure 612 generally represents any type or form ofinfrastructure capable of facilitating communication between one or morecomponents of a computing device. Examples of communicationinfrastructure 612 include, without limitation, a communication bus(such as an Industry Standard Architecture (ISA), Peripheral ComponentInterconnect (PCI), PCI Express (PCIe), or similar bus) and a network.

Memory controller 618 generally represents any type or form of devicecapable of handling memory or data or controlling communication betweenone or more components of computing system 610. For example, in certainembodiments memory controller 618 may control communication betweenprocessor 614, system memory 616, and 1/O controller 620 viacommunication infrastructure 612.

I/O controller 620 generally represents any type or form of modulecapable of coordinating and/or controlling the input and outputfunctions of a computing device. For example, in certain embodiments I/Ocontroller 620 may control or facilitate transfer of data between one ormore elements of computing system 610, such as processor 614, systemmemory 616, communication interface 622, display adapter 626, inputinterface 630, and storage interface 634.

Communication interface 622 broadly represents any type or form ofcommunication device or adapter capable of facilitating communicationbetween exemplary computing system 610 and one or more additionaldevices. For example, in certain embodiments communication interface 622may facilitate communication between computing system 610 and a privateor public network including additional computing systems. Examples ofcommunication interface 622 include, without limitation, a wired networkinterface (such as a network interface card), a wireless networkinterface (such as a wireless network interface card), a modem, and anyother suitable interface. In at least one embodiment, communicationinterface 622 may provide a direct connection to a remote server via adirect link to a network, such as the Internet. Communication interface622 may also indirectly provide such a connection through, for example,a local area network (such as an Ethernet network), a personal areanetwork, a telephone or cable network, a cellular telephone connection,a satellite data connection, or any other suitable connection.

In certain embodiments, communication interface 622 may also represent ahost adapter configured to facilitate communication between computingsystem 610 and one or more additional network or storage devices via anexternal bus or communications channel. Examples of host adaptersinclude, without limitation, Small Computer System Interface (SCSI) hostadapters, Universal Serial Bus (USB) host adapters, Institute ofElectrical and Electronics Engineers (IEEE) 1394 host adapters, AdvancedTechnology Attachment (ATA), Parallel ATA (PATA), Serial ATA (SATA), andExternal SATA (eSATA) host adapters, Fibre Channel interface adapters,Ethernet adapters, or the like. Communication interface 622 may alsoallow computing system 610 to engage in distributed or remote computing.For example, communication interface 622 may receive instructions from aremote device or send instructions to a remote device for execution.

As illustrated in FIG. 6, computing system 610 may also include at leastone display device 624 coupled to communication infrastructure 612 via adisplay adapter 626. Display device 624 generally represents any type orform of device capable of visually displaying information forwarded bydisplay adapter 626. Similarly, display adapter 626 generally representsany type or form of device configured to forward graphics, text, andother data from communication infrastructure 612 (or from a framebuffer, as known in the art) for display on display device 624.

As illustrated in FIG. 6, exemplary computing system 610 may alsoinclude at least one input device 628 coupled to communicationinfrastructure 612 via an input interface 630. Input device 628generally represents any type or form of input device capable ofproviding input, either computer or human generated, to exemplarycomputing system 610. Examples of input device 628 include, withoutlimitation, a keyboard, a pointing device, a speech recognition device,or any other input device.

As illustrated in FIG. 6, exemplary computing system 610 may alsoinclude a primary storage device 632 and a backup storage device 633coupled to communication infrastructure 612 via a storage interface 634.Storage devices 632 and 633 generally represent any type or form ofstorage device or medium capable of storing data and/or othercomputer-readable instructions. For example, storage devices 632 and 633may be a magnetic disk drive (e.g., a so-called hard drive), a solidstate drive, a floppy disk drive, a magnetic tape drive, an optical diskdrive, a flash drive, or the like. Storage interface 634 generallyrepresents any type or form of interface or device for transferring databetween storage devices 632 and 633 and other components of computingsystem 610. In one example, database 120 from FIG. 1 may be stored inprimary storage device 632.

In certain embodiments, storage devices 632 and 633 may be configured toread from and/or write to a removable storage unit configured to storecomputer software, data, or other computer-readable information.Examples of suitable removable storage units include, withoutlimitation, a floppy disk, a magnetic tape, an optical disk, a flashmemory device, or the like. Storage devices 632 and 633 may also includeother similar structures or devices for allowing computer software,data, or other computer-readable instructions to be loaded intocomputing system 610. For example, storage devices 632 and 633 may beconfigured to read and write software, data, or other computer-readableinformation. Storage devices 632 and 633 may also be a part of computingsystem 610 or may be a separate device accessed through other interfacesystems.

Many other devices or subsystems may be connected to computing system610. Conversely, all of the components and devices illustrated in FIG. 6need not be present to practice the embodiments described and/orillustrated herein. The devices and subsystems referenced above may alsobe interconnected in different ways from that shown in FIG. 6. Computingsystem 610 may also employ any number of software, firmware, and/orhardware configurations. For example, one or more of the exemplaryembodiments disclosed herein may be encoded as a computer program (alsoreferred to as computer software, software applications,computer-readable instructions, or computer control logic) on acomputer-readable medium. The term “computer-readable medium,” as usedherein, generally refers to any form of device, carrier, or mediumcapable of storing or carrying computer-readable instructions. Examplesof computer-readable media include, without limitation,transmission-type media, such as carrier waves, and non-transitory-typemedia, such as magnetic-storage media (e.g., hard disk drives, tapedrives, and floppy disks), optical-storage media (e.g., Compact Disks(CDs), Digital Video Disks (DVDs), and BLU-RAY disks),electronic-storage media (e.g., solid-state drives and flash media), andother distribution systems.

The computer-readable medium containing the computer program may beloaded into computing system 610. All or a portion of the computerprogram stored on the computer-readable medium may then be stored insystem memory 616 and/or various portions of storage devices 632 and633. When executed by processor 614, a computer program loaded intocomputing system 610 may cause processor 614 to perform and/or be ameans for performing the functions of one or more of the exemplaryembodiments described and/or illustrated herein. Additionally oralternatively, one or more of the exemplary embodiments described and/orillustrated herein may be implemented in firmware and/or hardware. Forexample, computing system 610 may be configured as an ApplicationSpecific Integrated Circuit (ASIC) adapted to implement one or more ofthe exemplary embodiments disclosed herein.

FIG. 7 is a block diagram of an exemplary network architecture 700 inwhich client systems 710, 720, and 730 and servers 740 and 745 may becoupled to a network 750. As detailed above, all or a portion of networkarchitecture 700 may perform and/or be a means for performing, eitheralone or in combination with other elements, one or more of the stepsdisclosed herein (such as one or more of the steps illustrated in FIG.3). All or a portion of network architecture 700 may also be used toperform and/or be a means for performing other steps and features setforth in the instant disclosure.

Client systems 710, 720, and 730 generally represent any type or form ofcomputing device or system, such as exemplary computing system 610 inFIG. 6. Similarly, servers 740 and 745 generally represent computingdevices or systems, such as application servers or database servers,configured to provide various database services and/or run certainsoftware applications. Network 750 generally represents anytelecommunication or computer network including, for example, anintranet, a WAN, a LAN, a PAN, or the Internet. In one example, clientsystems 710, 720, and/or 730 and/or servers 740 and/or 745 may includeall or a portion of system 100 from FIG. 1.

As illustrated in FIG. 7, one or more storage devices 760(1)-(N) may bedirectly attached to server 740. Similarly, one or more storage devices770(1)-(N) may be directly attached to server 745. Storage devices760(1)-(N) and storage devices 770(1)-(N) generally represent any typeor form of storage device or medium capable of storing data and/or othercomputer-readable instructions. In certain embodiments, storage devices760(1)-(N) and storage devices 770(1)-(N) may represent Network-AttachedStorage (NAS) devices configured to communicate with servers 740 and 745using various protocols, such as Network File System (NFS), ServerMessage Block (SMB), or Common Internet File System (CIFS).

Servers 740 and 745 may also be connected to a Storage Area Network(SAN) fabric 780. SAN fabric 780 generally represents any type or formof computer network or architecture capable of facilitatingcommunication between a plurality of storage devices. SAN fabric 780 mayfacilitate communication between servers 740 and 745 and a plurality ofstorage devices 790(1)-(N) and/or an intelligent storage array 795. SANfabric 780 may also facilitate, via network 750 and servers 740 and 745,communication between client systems 710, 720, and 730 and storagedevices 790(1)-(N) and/or intelligent storage array 795 in such a mannerthat devices 790(1)-(N) and array 795 appear as locally attached devicesto client systems 710, 720, and 730. As with storage devices 760(1)-(N)and storage devices 770(1)-(N), storage devices 790(1)-(N) andintelligent storage array 795 generally represent any type or form ofstorage device or medium capable of storing data and/or othercomputer-readable instructions.

In certain embodiments, and with reference to exemplary computing system610 of FIG. 6, a communication interface, such as communicationinterface 622 in FIG. 6, may be used to provide connectivity betweeneach client system 710, 720, and 730 and network 750. Client systems710, 720, and 730 may be able to access information on server 740 or 745using, for example, a web browser or other client software. Suchsoftware may allow client systems 710, 720, and 730 to access datahosted by server 740, server 745, storage devices 760(1)-(N), storagedevices 770(1)-(N), storage devices 790(1)-(N), or intelligent storagearray 795. Although FIG. 7 depicts the use of a network (such as theInternet) for exchanging data, the embodiments described and/orillustrated herein are not limited to the Internet or any particularnetwork-based environment.

In at least one embodiment, all or a portion of one or more of theexemplary embodiments disclosed herein may be encoded as a computerprogram and loaded onto and executed by server 740, server 745, storagedevices 760(1)-(N), storage devices 770(1)-(N), storage devices790(1)-(N), intelligent storage array 795, or any combination thereof.All or a portion of one or more of the exemplary embodiments disclosedherein may also be encoded as a computer program, stored in server 740,run by server 745, and distributed to client systems 710, 720, and 730over network 750.

As detailed above, computing system 610 and/or one or more components ofnetwork architecture 700 may perform and/or be a means for performing,either alone or in combination with other elements, one or more steps ofan exemplary method for categorizing electronic messages for compliancereviews.

While the foregoing disclosure sets forth various embodiments usingspecific block diagrams, flowcharts, and examples, each block diagramcomponent, flowchart step, operation, and/or component described and/orillustrated herein may be implemented, individually and/or collectively,using a wide range of hardware, software, or firmware (or anycombination thereof) configurations. In addition, any disclosure ofcomponents contained within other components should be consideredexemplary in nature since many other architectures can be implemented toachieve the same functionality.

In some examples, all or a portion of exemplary system 100 in FIG. 1 mayrepresent portions of a cloud-computing or network-based environment.Cloud-computing environments may provide various services andapplications via the Internet. These cloud-based services (e.g.,software as a service, platform as a service, infrastructure as aservice, etc.) may be accessible through a web browser or other remoteinterface. Various functions described herein may be provided through aremote desktop environment or any other cloud-based computingenvironment.

In various embodiments, all or a portion of exemplary system 100 in FIG.1 may facilitate multi-tenancy within a cloud-based computingenvironment. In other words, the software modules described herein mayconfigure a computing system (e.g., a server) to facilitatemulti-tenancy for one or more of the functions described herein. Forexample, one or more of the software modules described herein mayprogram a server to enable two or more clients (e.g., customers) toshare an application that is running on the server. A server programmedin this manner may share an application, operating system, processingsystem, and/or storage system among multiple customers (i.e., tenants).One or more of the modules described herein may also partition dataand/or configuration information of a multi-tenant application for eachcustomer such that one customer cannot access data and/or configurationinformation of another customer.

According to various embodiments, all or a portion of exemplary system100 in FIG. 1 may be implemented within a virtual environment. Forexample, the modules and/or data described herein may reside and/orexecute within a virtual machine. As used herein, the term “virtualmachine” generally refers to any operating system environment that isabstracted from computing hardware by a virtual machine manager (e.g., ahypervisor). Additionally or alternatively, the modules and/or datadescribed herein may reside and/or execute within a virtualizationlayer. As used herein, the term “virtualization layer” generally refersto any data layer and/or application layer that overlays and/or isabstracted from an operating system environment. A virtualization layermay be managed by a software virtualization solution (e.g., a filesystem filter) that presents the virtualization layer as though it werepart of an underlying base operating system. For example, a softwarevirtualization solution may redirect calls that are initially directedto locations within a base file system and/or registry to locationswithin a virtualization layer.

In some examples, all or a portion of exemplary system 100 in FIG. 1 mayrepresent portions of a mobile computing environment. Mobile computingenvironments may be implemented by a wide range of mobile computingdevices, including mobile phones, tablet computers, e-book readers,personal digital assistants, wearable computing devices (e.g., computingdevices with a head-mounted display, smartwatches, etc.), and the like.In some examples, mobile computing environments may have one or moredistinct features, including, for example, reliance on battery power,presenting only one foreground application at any given time, remotemanagement features, touchscreen features, location and movement data(e.g., provided by Global Positioning Systems, gyroscopes,accelerometers, etc.), restricted platforms that restrict modificationsto system-level configurations and/or that limit the ability ofthird-party software to inspect the behavior of other applications,controls to restrict the installation of applications (e.g., to onlyoriginate from approved application stores), etc. Various functionsdescribed herein may be provided for a mobile computing environmentand/or may interact with a mobile computing environment.

In addition, all or a portion of exemplary system 100 in FIG. 1 mayrepresent portions of, interact with, consume data produced by, and/orproduce data consumed by one or more systems for information management.As used herein, the term “information management” may refer to theprotection, organization, and/or storage of data. Examples of systemsfor information management may include, without limitation, storagesystems, backup systems, archival systems, replication systems, highavailability systems, data search systems, virtualization systems, andthe like.

In some embodiments, all or a portion of exemplary system 100 in FIG. 1may represent portions of, produce data protected by, and/or communicatewith one or more systems for information security. As used herein, theterm “information security” may refer to the control of access toprotected data. Examples of systems for information security mayinclude, without limitation, systems providing managed securityservices, data loss prevention systems, identity authentication systems,access control systems, encryption systems, policy compliance systems,intrusion detection and prevention systems, electronic discoverysystems, and the like.

According to some examples, all or a portion of exemplary system 100 inFIG. 1 may represent portions of, communicate with, and/or receiveprotection from one or more systems for endpoint security. As usedherein, the term “endpoint security” may refer to the protection ofendpoint systems from unauthorized and/or illegitimate use, access,and/or control. Examples of systems for endpoint protection may include,without limitation, anti-malware systems, user authentication systems,encryption systems, privacy systems, spam-filtering services, and thelike.

The process parameters and sequence of steps described and/orillustrated herein are given by way of example only and can be varied asdesired. For example, while the steps illustrated and/or describedherein may be shown or discussed in a particular order, these steps donot necessarily need to be performed in the order illustrated ordiscussed. The various exemplary methods described and/or illustratedherein may also omit one or more of the steps described or illustratedherein or include additional steps in addition to those disclosed.

While various embodiments have been described and/or illustrated hereinin the context of fully functional computing systems, one or more ofthese exemplary embodiments may be distributed as a program product in avariety of forms, regardless of the particular type of computer-readablemedia used to actually carry out the distribution. The embodimentsdisclosed herein may also be implemented using software modules thatperform certain tasks. These software modules may include script, batch,or other executable files that may be stored on a computer-readablestorage medium or in a computing system. In some embodiments, thesesoftware modules may configure a computing system to perform one or moreof the exemplary embodiments disclosed herein.

In addition, one or more of the modules described herein may transformdata, physical devices, and/or representations of physical devices fromone form to another. For example, one or more of the modules recitedherein may receive a batch of electronic messages to be transformed,transform the batch of electronic messages into a sorted list ofelectronic messages, output a result of the transformation to aninterface used by a compliance reviewer, use the result of thetransformation to display the sorted list of electronic messages, andstore the result of the transformation to a database. Additionally oralternatively, one or more of the modules recited herein may transform aprocessor, volatile memory, non-volatile memory, and/or any otherportion of a physical computing device from one form to another byexecuting on the computing device, storing data on the computing device,and/or otherwise interacting with the computing device.

The preceding description has been provided to enable others skilled inthe art to best utilize various aspects of the exemplary embodimentsdisclosed herein. This exemplary description is not intended to beexhaustive or to be limited to any precise form disclosed. Manymodifications and variations are possible without departing from thespirit and scope of the instant disclosure. The embodiments disclosedherein should be considered in all respects illustrative and notrestrictive. Reference should be made to the appended claims and theirequivalents in determining the scope of the instant disclosure.

Unless otherwise noted, the terms “connected to” and “coupled to” (andtheir derivatives), as used in the specification and claims, are to beconstrued as permitting both direct and indirect (i.e., via otherelements or components) connection. In addition, the terms “a” or “an,”as used in the specification and claims, are to be construed as meaning“at least one of.” Finally, for ease of use, the terms “including” and“having” (and their derivatives), as used in the specification andclaims, are interchangeable with and have the same meaning as the word“comprising.”

What is claimed is:
 1. A computer-implemented method for categorizingelectronic messages for compliance reviews, at least a portion of themethod being performed by a computing device comprising at least oneprocessor and a memory, the method comprising: identifying, by thecomputing device and as part of a compliance review for an organization,an uncategorized electronic message sent or received by a superviseduser within the organization; comparing, by the computing device, theuncategorized electronic message with information gathered frompreviously categorized electronic messages sent or received bysupervised users within the organization; determining, by the computingdevice and based at least in part on the comparison, a relevance levelof the uncategorized electronic message with respect to the compliancereview, wherein the relevance level comprises a first relevance levelthat is above a relevance threshold and a second relevance level that isbelow the relevance threshold; determining, by the computing device,whether the uncategorized electronic message was received from adistribution list by the supervised user within the organization,wherein upon determining that the uncategorized message was receivedfrom the distribution list, the uncategorized electronic message iscategorized as not relevant with respect to the compliance reviewirrespective of the determined relevance level; receiving, by thecomputing device and from a compliance reviewer, feedback indicatingwhether the determined relevance level is correct; updating, by thecomputing device, the previously gathered information based on thefeedback from the compliance reviewer; and presenting, by the computingdevice in an interface, a list of electronic messages ranked accordingto the determined relevance level, wherein presenting the list includesapplying visual highlighting to the electronic messages corresponding tothe first relevance level, thereby decreasing a likelihood of a reviewermissing relevant electronic messages above the relevance threshold. 2.The computer-implemented method of claim 1, wherein the compliancereview comprises an examination, by the compliance reviewer, of at leasta subset of all electronic messages sent or received by the supervisedusers within the organization, wherein in order to determine whether thesubset of electronic messages sent or received by the supervised usersincludes any evidence of at least one activity by the supervised users.3. The computer-implemented method of claim 1, wherein determining therelevance level of the uncategorized electronic message furthercomprises: examining the uncategorized electronic message for anyevidence indicating whether the uncategorized electronic message is acommunication comprising the at least one of a scheduled report, anevent invitation, or an announcement sent or received by the supervisedusers; and determining, based at least in part on the examination of theuncategorized electronic message, the relevance level of theuncategorized electronic message.
 4. The computer-implemented method ofclaim 3, wherein determining the relevance level of the uncategorizedelectronic message further comprises at least one of: assigning, to theuncategorized electronic message, the first relevance level due at leastin part to examined evidence indicating that the uncategorizedelectronic message is not the communication, wherein the first relevancelevel corresponds to electronic messages that are not included in thecommunication; or assigning, to the uncategorized electronic message,the second relevance level due at least in part to examined evidenceindicating that the uncategorized electronic message is thecommunication, wherein the second relevance level corresponds toelectronic messages that are included in the communication.
 5. Thecomputer-implemented method of claim 1, wherein comparing theuncategorized electronic message with the information gathered from thepreviously categorized electronic messages comprises comparing arecipient of the uncategorized electronic message to a recipient of atleast one previously categorized electronic message.
 6. Thecomputer-implemented method of claim 1, wherein comparing theuncategorized electronic message with the information gathered from thepreviously categorized electronic messages comprises comparing a senderof the uncategorized electronic message to a sender of at least onepreviously categorized electronic message.
 7. The computer-implementedmethod of claim 1, wherein comparing the uncategorized electronicmessage with the information gathered from the previously categorizedelectronic messages comprises comparing a keyword in the uncategorizedelectronic message to a keyword in at least one previously categorizedelectronic message.
 8. The computer-implemented method of claim 1,wherein comparing the uncategorized electronic message with theinformation gathered from the previously categorized electronic messagescomprises comparing a word frequency statistic derived from theuncategorized electronic message to a word frequency statistic derivedfrom at least one previously categorized electronic message.
 9. Thecomputer-implemented method of claim 1, wherein comparing theuncategorized electronic message with the information gathered from thepreviously categorized electronic messages comprises at least one of:comparing metadata about the uncategorized electronic message tometadata from at least one previously categorized electronic message;comparing a subject of the uncategorized electronic message to a subjectfrom at least one previously categorized electronic message; comparing adirection of the uncategorized electronic message relative to theorganization to a direction from at least one previously categorizedelectronic message; comparing a domain of a sender the uncategorizedelectronic message to a domain of a sender from at least one previouslycategorized electronic message; and comparing a domain of a recipientthe uncategorized electronic message to a domain of a recipient from atleast one previously categorized electronic message.
 10. Thecomputer-implemented method of claim 1, further comprising: collectingrelevance levels assigned to the previously categorized electronicmessages; comparing the relevance level of the uncategorized electronicmessage to the relevance levels assigned to the previously categorizedelectronic messages; ranking, based at least in part on the relevancelevels, a set of electronic messages that includes the uncategorizedelectronic message and the previously categorized electronic messages;and providing the ranked set of electronic messages to the compliancereviewer as part of the compliance review.
 11. The computer-implementedmethod of claim 1, further comprising at least one of: deleting theinformation gathered from the previously categorized electronic messagesupon completion of the compliance review and initiation of a newcompliance review for the organization; and deleting the informationgathered from the previously categorized electronic messages due atleast in part to the information being out of date.
 12. Thecomputer-implemented method of claim 1, wherein: determining therelevance level of the uncategorized electronic message comprisesdetermining that the uncategorized electronic message is substantiallyrelevant to the compliance review; receiving the feedback indicatingwhether the determined relevance level is correct comprises receivingfeedback indicating that the relevance level is incorrect and theuncategorized electronic message is substantially irrelevant to thecompliance review; and updating the previously gathered informationbased on the feedback comprises updating the previously gatheredinformation to indicate that the uncategorized electronic message issubstantially irrelevant to the compliance review.
 13. Thecomputer-implemented method of claim 1, wherein determining therelevance level of the uncategorized electronic message furthercomprises: determining that the uncategorized electronic message issubstantially irrelevant to the compliance review; receiving thefeedback indicating whether the determined relevance level is correctcomprises receiving feedback indicating that the relevance level isincorrect and the uncategorized electronic message is substantiallyrelevant to the compliance review; and updating the previously gatheredinformation based on the feedback comprises updating the previouslygathered information to indicate that the uncategorized electronicmessage is substantially relevant to the compliance review.
 14. A systemfor categorizing electronic messages for compliance reviews, the systemcomprising: an identification module, stored in memory, that identifies,as part of a compliance review for an organization, an uncategorizedelectronic message sent or received by a supervised user within theorganization; a comparison module, stored in memory, that compares theuncategorized electronic message with information gathered frompreviously categorized electronic messages sent or received bysupervised users within the organization; a determination module, storedin memory, that: determines, based at least in part on the comparison, arelevance level of the uncategorized electronic message with respect tothe compliance review, wherein the relevance level comprises a firstrelevance level that is above a relevance threshold and a secondrelevance level that is below the relevance threshold; determineswhether the uncategorized electronic message was received from adistribution list by the supervised user within the organization,wherein upon determining that the uncategorized message was receivedfrom the distribution list, the uncategorized electronic message iscategorized as not relevant with respect to the compliance reviewirrespective of the determined relevance level; and presents, in aninterface, a list of electronic messages ranked according to thedetermined relevance level, wherein presenting the list includesapplying visual highlighting to the electronic messages corresponding tothe first relevance level, thereby decreasing a likelihood of a reviewermissing relevant electronic messages above the relevance threshold; areceiving module, stored in memory, that receives, from a compliancereviewer, feedback indicating whether the determined relevance level iscorrect; an updating module, stored in memory, that updates thepreviously gathered information based on the feedback from thecompliance reviewer; and at least one physical processor configured toexecute the identification module, the comparison module, thedetermination module, the receiving module, and the updating module. 15.The system of claim 14, wherein the compliance review comprises anexamination, by the compliance reviewer, of at least a subset of allelectronic messages sent or received by the supervised users within theorganization, wherein in order to determine whether the subset ofelectronic messages sent or received by the supervised users includesany evidence of least one activity by the supervised users.
 16. Thesystem of claim 14, wherein the determination module further determinesthe relevance level of the uncategorized electronic message by:examining the uncategorized electronic message for any evidenceindicating whether the uncategorized electronic message is acommunication comprising the at least one of a scheduled report, anevent invitation, or an announcement sent or received by the supervisedusers; and determining, based at least in part on the examination of theuncategorized electronic message, the relevance level of theuncategorized electronic message.
 17. The system of claim 16, whereinthe determination module further determines the relevance level of theuncategorized electronic message by at least one of: assigning, to theuncategorized electronic message, the first relevance level due at leastin part to examined evidence indicating that the uncategorizedelectronic message is not the communication, wherein the first relevancelevel corresponds to electronic messages that are not included in thecommunication; or assigning, to the uncategorized electronic message,the second relevance level due at least in part to examined evidenceindicating that the uncategorized electronic message is thecommunication, wherein the second relevance level corresponds toelectronic messages that are included in the communication.
 18. Thesystem of claim 14, wherein the comparison module compares theuncategorized electronic message with the information gathered from thepreviously categorized electronic messages by comparing a recipient ofthe uncategorized electronic message to a recipient of at least onepreviously categorized electronic message.
 19. The system of claim 14,wherein the comparison module compares the uncategorized electronicmessage with the information gathered from the previously categorizedelectronic messages by comparing a sender of the uncategorizedelectronic message to a sender of at least one previously categorizedelectronic message.
 20. A non-transitory computer-readable mediumcomprising one or more computer-readable instructions that, whenexecuted by at least one processor of a computing device comprising amemory, cause the computing device to: identify, as part of a compliancereview for an organization, an uncategorized electronic message sent orreceived by a supervised user within the organization; compare theuncategorized electronic message with information gathered frompreviously categorized electronic messages sent or received bysupervised users within the organization; determine, based at least inpart on the comparison, a relevance level of the uncategorizedelectronic message with respect to the compliance review, wherein therelevance level comprises a first relevance level that is above arelevance threshold and a second relevance level that is below therelevance threshold; determine whether the uncategorized electronicmessage was received from a distribution list by the supervised userwithin the organization, wherein upon determining that the uncategorizedmessage was received from the distribution list, the uncategorizedelectronic message is categorized as not relevant with respect to thecompliance review irrespective of the determined relevance level;receive, from a compliance reviewer, feedback indicating whether thedetermined relevance level is correct; update the previously gatheredinformation based on the feedback from the compliance reviewer; andpresent, in an interface, a list of electronic messages ranked accordingto the determined relevance level, wherein presenting the list includesapplying visual highlighting to the electronic messages corresponding tothe first relevance level, thereby decreasing a likelihood of a reviewermissing relevant electronic messages above the relevance threshold.